Abstract
Radar data are essential to convection nowcasting and nudging-based radar data assimilation through diabatic initialization is one of the most effective approaches for forecasting convective systems with numerical weather prediction (NWP) models, used at several advanced global weather centers. It is desired to assess the uncertainty and physical consistency of this assimilation process. This paper investigated impacts of relaxation coefficient, radar data update intervals and continuous assimilation time duration and addressed the key issues and possible solutions of the radar data assimilation based on the WRF hydrometeor and latent heat nudging (HLHN) developed at the National Center for Atmospheric Research (NCAR). It is revealed that excessively large relaxation coefficient forced the model to observations with a tendency greater than the physical terms of the convection, causing the dynamic imbalances and serious convection “ramp-down” right after the free forecast starts. Assimilating high update frequency radar data can make the tendency terms moderate and sustained thereby maintaining the assimilation effect and reducing fortuitous convection. HLHN requires a minimum continuous assimilation duration to contain the initial forced disturbance of the model. For a summer Meiyu precipitation case studied, the minimum duration is ~1 h. Appropriate selection of the HLHN parameters is able to effectively improve the temperature, humidity, and dynamic fields of the model. In addition, several issues still remain to be solved to further enhance HLHN.
Highlights
Introduction published maps and institutional affilConvection is one of the most unstable chaotic and nonlinear components of atmospheric processes, and convection nowcasting has always been a hot and challenging research topic in meteorological research and operations
In the Weather Research and Forecasting model (WRF) model, the calculation of reflectivity depends on the details of the microphysical scheme used, especially the treatment of liquid water and ice
For the purpose of isolating the contribution of different factors and achieving the optimal effect of WRF-FDDA, we study the sensitivity of different hydrometeor and latent heat nudging (HLHN) parameters by building observing system simulation experiments (OSSEs)
Summary
Introduction published maps and institutional affilConvection is one of the most unstable chaotic and nonlinear components of atmospheric processes, and convection nowcasting has always been a hot and challenging research topic in meteorological research and operations. Traditional, nowcasting is usually considered to use the previously initiated model forecast or reanalysis data as a background, combined with observational information from different measurements, using a variety of methods to quickly forecast the weather conditions from the current moment to several hours later [1]. In the past few years, advances in weather radar observation techniques have led to valuable progress in methods based on numerical weather prediction (NWP) and radar echo extrapolation [2,3,4]. Weather radar is the only instrument that perform frequent and refined sampling of convective storms. Developing an accurate method to assimilate the radar observation into numerical models remains a difficult task [5]. Developing an accurate method to assimilate the radar observation into numerical models remains a difficult task [5]. iations.
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